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In the midst of a pandemic, in the midst of the global effort to develop effective vaccines and anti-virals for SARS-CoV-2—yet, paradoxically, also in the midst of a surreal moment in history where the very science that can save millions is assailed if the facts and truth conflict with political mantra—we nonetheless can celebrate. Reminding us all of the importance and relevance of science, today, October 19, 2020, we celebrate the announcement of the draft human proteome in the opening talk at HUPO CONNECT by the First Chair of the Human Proteome Project (HPP), Dr Gil Omenn, with a virtual issue of the Journal of Proteome Research (https://pubs.acs.org/page/jprobs/vi/humanproteome). In the virtual issue the editors have compiled 60 of the most significant papers published in the Journal over the past decade on the human proteome project reflecting the diversity of the C-HPP and B/D-HPP teams, regions, approaches, impact and achievement.
The neXtProt database posted the landmark human proteome data release covering 90% of the human proteome on 17th January, 20201, which is now reported by the HPP Consortium in Nature Communications by Adhikari et al 20202. In the companion annual human proteome metrics paper by Gil Omenn et al 20203 reporting this year’s progress of the HPP, the underlying data is presented in depth. The metrics paper will be published in the 8th Special Issue of the Journal of Proteome Research dedicated to the HPP in December 2020, with the ASAP preprint online today leading this HPP Virtual Issue and with a commentary editorial by Chris Overall4.
The human proteome was identified by HPP global research teams and scientists from the wider scientific community and assembled by the Chromosome Centric-HPP (C-HPP) and the HPP Knowledgebase Pillar data curators from neXtProt PeptideAtlas, and MassIVE. The C-HPP was established in 2010 as the major initiative of the HPP to identify at least one protein form (proteoform) from each of the protein-encoding genes in the human genome. For the next high-fidelity compendium of the full human proteome and to develop a broader understanding of life, human conscience, and disease, proteomics needs more data, more patients, more scientists, and more doctors to understand life, individuality, personality and disease—science needs us all, but now, more than ever, humanity needs more science
2. Subash Adhikari, Edouard Nice, Eric Deutsch, Lydie Lane, Gilbert Omenn, Steve Pennington, Young-ki Paik, Christopher Overall, Fernando Corrales, Ileana Cristea, Jennifer Van Eyk, Mathias Uhlen, Cecilia Lindskog, Daniel Chan, Amos Bairoch, James Waddington, Joshua Justice, Joshua LaBaer, Henry Rodriguez, Fuchu He, Markus Kostrzewa, Peipei Ping, Rebekah Gundry, Peter Stewart, Sanjeeva Srivastava, Sudhir Srivastava, Fabio Nogueira, Gilberto Domont, Yves Vandenbrouck, Maggie Lam, Sara Wennersten, Juan Antonio Vizcaino, Marc Wilkins, Jochen Schwenk, Emma Lundberg, Nuno Bandeira, György Marko-Varga, Susan Weintraub, Charles Pineau, Ulrike Kusebauch, Robert Moritz, Seong Beom Ahn, Magnas Palmblad, Michael Snyder, Ruedi Aebersold, and Mark Baker. A High-Stringency Blueprint of the Human Proteome, Nat. Communications, 2020, doi.org/10.1038/s41467-020-19045-9.
3. Omenn G. S.; Lane L.; Overall C. M.; Cristea I. M.; Corrales F. J.; Lindskog C.; Paik Y-K.; Van Eyk J. E.; Liu S.; Pennington S.; Snyder M.P.; Baker M.; Bandeira N.; Aebersold, R.; Moritz, R.L.; Deutsch EW. Research on The Human Proteome Reaches a Major Milestone: >90% of Predicted Human Proteins Now Credibly Detected, According to the HUPO Human Proteome Project. J Proteome Res. 2020, Sep 15. doi: 10.1021/acs.jproteome.0c00485.
4. Overall, C.M. J Proteome Res. 2020, October 19. The HUPO High-Stringency Inventory of Humanity’s Shared Human Proteome Revealed. https://pubs.acs.org/doi/full/10.1021/acs.jproteome.0c00794.
The 2020 Metrics of the HUPO Human Proteome Project (HPP) effort to credibly detect every protein of the human proteome has been released (see https://pubs.acs.org/doi/10.1021/acs.jproteome.0c00485). This report now provides evidence for detected expression for >90% of the 19,773 predicted proteins coded in the human genome. The HPP annually reports on the progress made throughout the world toward credibly identifying and characterizing the complete human protein parts list and promoting proteomics as an integral part of multiomics studies in medicine and the life sciences. The 2020 metrics paper describes the credibly detected proteins (PE1 level) as well as the 4 other PE levels of protein evidence in a central repository for community sharing of these results. With the neXtProt release of 2020−01, 17,874 genes encoding proteins are classified as PE1 and having strong protein-level evidence. This PE1 level is up 180 proteins from 17,694 one year earlier and represent 90.4% of the 19,773 predicted coding genes (all PE1,2,3,4 proteins in neXtProt). Conversely, the number of neXtProt PE2,3,4 proteins, termed the “missing proteins” (MPs), was reduced by 230 from 2129 to 1899 since the previous year’s release neXtProt 2019−01. PeptideAtlas is the primary source of uniform reanalysis of raw mass spectrometry (MS) data for neXtProt, supplemented this year with extensive data from the MS repository MassIVE. The mass spectrometry data knowledge bases promoted 362 and 84 canonical proteins (PeptideAtlas and MassIVE respectively) in the last year to increase the credibly identified proteins. The Human Protein Atlas also released new protein detection repositories (based on antibody binding data to human proteins) for Blood, Brain, and Metabolic Atlases. The Biology and Disease-driven (B/D)-HPP teams continue to pursue the identification of driver proteins that underlie disease states, the characterization of regulatory mechanisms controlling the functions of these proteins, their proteoforms, and their interactions.
Of the remaining “missing proteins”, hydrophobic proteins account for about 40% of these and are compounded by protein sequence structures that are difficult to extract credible peptides for high-stringency identification. These missing proteins include large families or groups including GPCR, zinc finger, homeobox, keratin-associated, and coiled-coil domain proteins. We expect novel strategies for finding missing proteins, characterizing the functions of already-detected “dark” proteins, and utilizing proteogenomics in precision medicine to be fruitful in the coming years.
In addition, the Journal of Proteome Research will produce a year-end virtual Issue with dozens of high-impact papers from the 7 annual special issues of JPR from the Human Proteome Project.
The Human Proteome Project (HPP) releases the first Human Proteome Organization (HUPO)-endorsed, high-stringency Human Proteome Blueprint in Nature Communications (see https://www.nature.com/articles/s41467-020-19045-9). Like the draft “shotgun” Human Genome Project of the Human Genome Organization (HUGO), the HPP has now reached a significant decadal milestone of >90% completion of the Human Proteome that is referred to as the human proteome “parts-list”. This effort recognizes significant community efforts that enabled data inspection and re-analysis, culminating in a high stringency (i.e., rigorous, exacting standards for post-acquisition data processing and protein inferences made from MS spectral data) HPP knowledge base (KB). Additionally, to illustrate the many parallel historical innovations made by the scientific community that have driven proteomics advances, HUPO has created a publicly available interactive historical timeline to be released coincident with publication of this article (hupo.org/Proteomics-Timeline).
The HPP’s mission is to reanalyze and integrate community proteomics data with high-stringency processes, bringing increased granularity to our molecular understanding of the dynamic nature of the proteome, including all its modifications, and their relation to human biology and disease. This mission aligns closely with HUPO’s motto “translating the code of life”, providing crucial information that genomics per se cannot deliver. Completion of the HPP will enhance our understanding of human molecular and cellular biology, laying better foundations for diagnostic, prognostic, therapeutic and precision medicine applications.
In 2010, the Human Proteome Organization launched the Human Proteome Project (HPP), as an international endeavor to create a framework for global collaboration, data sharing and quality assurance, enhancing accurate annotation of the genome-encoded proteome. Over the last decade, the key resources of the HPP (the Human Protein Atlas, PeptideAtlas, MassIVE and neXtProt knowledge bases) have driven the development and refinement of guidelines and metrics to understand the definitive identification of any protein of the human proteome. Their high-stringency reanalysis of community data led to the current status of >90% identification completion rate of the Human Proteome. This knowledge is essential to discern the proteome’s role in health and disease. Here, on behalf of the proteomics community, we report the inaugural high-stringency human proteome project blueprint, illustrating roles in the diagnosis and treatment of cancers, cardiovascular and infectious disease pathologies.
The Human Immuno-Peptidome Project (HIPP) was launched in 2015 under the aegis of HUPO and B/D-HPP (https://hupo.org/Human-Immuno-Peptidome-Project). The vision of HIPP is to map the entire repertoire of peptides presented by HLA molecules using mass spectrometry technologies, and make its robust analysis accessible to any immunologist, clinical-investigator and other researchers around the globe. The main pillars of the HIPP program are the following: (1) method and technology development, (2) standardization, (3) effective data sharing, and (4) education . Etienne Caron and Michal Bassani-Sternberg are the current HIPP Chair and co-Chair. Under their leadership, the following short-term and middle-term goals were determined:
Since its foundation, two international HIPP workshops and one summer course have been successfully organized to move forward the field of immunopeptidomics from a community perspective.
With the expanding goals of HIPP and the increasing interest of the scientific community, we seek to engage two strong, well-organized, strategic, vibrant, enthusiastic, goal-oriented immunopeptidomics researchers who would be suitable candidates to the Chair and co-Chair positions. HIPP is keen to ensure regional, gender and early career scientist equity across its management structures.
The HIPP Chair and co-Chair position is a 2-year term (restricted to 4 consecutive years) and will commence in 2021. The responsibilities of the Chair and co-Chair can be summarised under the following areas:
1. Leadership. The overarching role of the Chair is to provide leadership, he/she must be an effective strategist and a good networker. The co-Chair will assist and support the HIPP Chair.
2. Committee. The first immediate responsibilities of the Chair/co-Chair will be to establish a HIPP Committee. The Committee will be composed of several members including a Treasurer who will manage the finances (currently in a HUPO bank account). The Committee will set short-term goals and will develop a plan to achieve those goals. The Chair/co-Chair will make the most of their committee members and will review the committee’s performance and identify and manage the process for renewal of the committee through recruitment of new members.
3. Coordination. The Chair/co-Chair will make sure that each meeting is planned effectively. They will co-ordinate the Committee to ensure that appropriate procedures are in place for the effective management of HIPP.
4. Representation. The Chair/co-Chair may from time to time be called upon to represent HIPP and sometimes be its spokesperson at, for example, HUPO meetings. The Chair/co-Chair will also be responsible for reporting HIPP’s annual progress to HPP/BD-HPP upon request by HUPO.
To apply, please submit a photo of yourself, and a brief (<1 page) vision statement outlining your background, previous activity in the HIPP initiative and why you are a suitable candidate for the HIPP leadership. Email vision statement to Michal.firstname.lastname@example.org before November 15, 2020.
Only HIPP members from academia can apply for the chair and co-chair positions, while members from industry can take part in the HIPP Committee. Applications will be reviewed by the Executive Committee of the B/D-HPP. In case of many applications, the current Chair and Co-Chair, together with the Executive Committee of the B/D-HPP will shortlist several most suitable candidates. The final list of candidates will be posted on the HIPP website, and the HIPP members will vote online for the suitable candidate. The applicant with the majority of votes will become the new Chair and the second place will become the co-Chair. The successful candidates will be announced shortly after the election.
1 Caron et al. (2017) A case for a human immuno-peptidome project consortium, Immunity 47, 203-208.
Dear HUPO colleagues and B/D-HPP team members:
I am happy to inform you that the B/D-HPP Executive Committee organized a 60 min BD-HPP team meeting on the last day (Thursday) of the HUPO connect.
We will use this meeting to discuss B/D-HPP goals, accomplishments, and ongoing EC efforts. These discussions will include the organization of additional annual virtual team meetings, HUPOST efforts, and modernization of the team chair election process with you.
We will also highlight four B/D-HPP teams, and short five-minute overview talks will be given by selected team members to review some of the organization and recent achievements of each initiative.
The meeting is open to all B/D-HPP investigators and other scientists interested in the B/D-HPP and free of charge.
Meeting time: Thursday, Oct 22, 3:00 - 4:00 PM UTC (i.e., 8:00 - 9:00 AM PDT; 11:00 AM - 12:00 PM EDT; 5:00 - 6:00 PM CET)
Please use the following link to find the corresponding time in other time zones: https://www.timeanddate.com/worldclock/fixedtime.html?iso=20201022T1500
We apologize for the inconvenient time of this meeting for several geographical areas. This time was selected to avoid overlap with the first three days of HUPO Connect and the HPP Day meeting that will follow shortly after our B/D-HPP meeting. We will record this meeting and will also try to schedule future meetings at different times.
Please join us! We need your voice and feedback for an interactive B/D-HPP and an effective progress for the next year.
Call in details via GoToMeeting are listed below signature.
Hope to see you soon!
The B/D-HPP EC Members:
Ileana Cristea (Chair)
Fernando Corrales (Past Chair)
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C-HPP PIC meeting at HUPO Connect
HUPO Connect 2020 will be held between October 19 and 22 and C-HPP PIC meeting is planned on Monday, October 19, 17:15 EST time. The topics to be discussed will be
We ask all chromosome teams to update their results and potential team changes on C-HPP Wiki until HUPO Connect 2020.
Highlights from the C-HPP neXt-MP50 chromosome team reports:
Nominations for Co-Chair of the HPP
Please register and join us in HUPO Connect 2020 and donate to neXt-prot (https://www.hupo.org/Donate)
The C-HPP EC wish you and for all your family to stay safe and healthy and let’s go find proteomic evidence and clues for new cures!
Maggie Lam, University of Colorado, USA
If you have not had the chance to read them, I would like to draw your attention to a number of excellent HUPOST articles contributed by members of our community:
We are actively looking for more articles about various developments and applications in proteomics in the coming months on the HUPOST column. We are especially interested in articles coauthored by early career investigators with their mentors in any proteomics or related fields. So please feel free to reach out to us if you would like to contribute a HUPOST article. We think this is a fantastic way to showcase your research, write about recent developments that excite you and issues you care about, and share it with the HUPO community.
Lastly, we are excited to be preparing a number of outreach activities for HUPO B/D-HPP in the coming months, including social media outreach via Twitter and webinars. Please contact me via email@example.com if you are interested in participating.
By Yuanwei Xu and Hui Zhang, Center for Biomarker Discovery & Translation, Johns Hopkins University
Glycosylation is one of the most important protein modifications, playing an essential role in almost every aspect of biological processes. Despite being an important subdiscipline of proteomics, the investigations on glycoproteomics lagged behind not due to lack of interest, but a dearth of suitable methods for characterizing the tremendously complex glycoproteome. Luckily, we are able to characterize glycoproteome in an unprecedented depth with the help of advanced technologies. Glycoproteomics has come to the spotlight of completing the picture of human proteome.
The Human Genome Project transforms biology and medicine through its integrated big science approach to decipher the roles of the human genome. The genome is almost identical across different human cells and throughout the life 1. However, the coded proteins from human genome in cells are much more dynamic and highly diversified to facilitate different biological functions2 3. In this context, the human proteome holds significantly more functional proteins than the coding capacity of 20,000 to 25,000 genes 1, which could be two to three orders of magnitude more complex (>1,000,000 protein species) 4 (Figure 1). The major mechanism responsible for the expansion of proteome is that proteins are subject to elaborative modifications 1 4.
Identifying proteins that are modified by specific chemical groups and determining their modification sites are the key focuses in characterization of human protein modifications. Ever since the 1980s 5, phosphorylation has been the most characterized protein modifications (based on the number of publications on the topic of different modifications in human from 1970 to 2020 at PubMed). Up to ~50,000 phosphorylation sites could be identified in each sample in a single phosphoproteomic experiment 6 7 8 9 10 11. Glycosylation, along with other modifications such as acetylation, ubiquitination and SUMOylation are more pervasively investigated because of technological advancements. Approximately, glycoproteins take up ~50% of the proteome 12, unmatched by any other protein modifications, since glycosylation is highly diversified to facilitate an assortment of functions 13. Despite the significance of protein glycosylation, the investigation of glycoproteome remains challenging due to the diversity of glycoprotein isoforms (glycoforms) when compared to other modifications. A rather comprehensive characterization of protein glycosylation site and the fine details of these site-specific glycans (including composition, sequence, branching, linkage, and anomericity) 14 would require for glycoprotein characterization.
Eukaryotic protein glycosylation is usually via two major types of linkages to proteins: N- and O-linked. N-linked glycoproteins are mainly attachment to asparagine residues by the covalent N-glycosidic bond. The general consensus peptide sequence for N-glycan is Asn-X-Ser/Thr (where X is any amino acid except proline) 15 16, while unusual glycosites with atypical motifis such as Asn-X-Val and Asn-X-Cys were found with low occupancy 17. Moreover, N-glycans in eukaryotic cells share a common core sequence, Manα1-3(Manα1-6)Manβ1-4GlcNAcβ1–4GlcNAcβ1–Asn 16. In contrast, O-glycosylation is linked to the hydroxyl groups of serine or threonine residues without an obvious motif preference 16. The initiating monosaccharides for O-linked glycosylation include galactosamine (GalNAc), mannose, galactose, fucose, glucose, and glucosamine (GlcNAc) 16, linear or branched oligosaccharide chains of various lengths could be further extended from the initiating monosaccharides. Both N- and O-linked glycosylation could be capped or modified with certain monosaccharides and chemical groups or substitutions 14. All of these aspects of glycosylation compounded protein glycosylation with a multitude of complexities. Other glycan-protein complexes form structures such as GPI-anchored glycoproteins and proteoglycans are also presented in eukaryotic systems.
Glycoproteomics focuses on the large-scale characterization of glycoproteins. Microarray-based approaches and mass spectrometry-based approaches have been used in glycoproteomics 14. Glycoprotein coding genes 18, purified glycoproteins 19, glycans 20 21 22 23, lectins 24 25 , or glycan-specific antibodies 26 have been used in microarray-based approach. Due to the plasticity of glycosylation, mass spectrometry (MS)-based glycoproteomics characterizes glycoproteins at different levels, including glycosylation sites (glycosites), glycans, and glycosite-specific glycans 27 28. Several enrichment methods have been published for these purposes, including hydrazide chemical tagging29 30, metabolic labeling 31 32, chemoenzymatic labeling 33, lectin chromatography 34 35 36, HILIC 37 38, ERLIC 39, “SimpleCell” technology with homogenized O-glycans 40 41 and EXoO42. The enriched glycosites, glycans, glycopeptides or glycoproteins would then be analyzed using different MS approaches, including CID-MS (often fragmenting glycans), ECD/ETD-MS (often cleaving peptide backbones), MALDI-MS (often for detailed glycan analysis using MSn), and HCD-MS (often generating both peptide backbone and glycan fragment ions). The MS results would then be searched against known databases to identify glycosylation sites, glycans, glycans at each glycosite, and the abundance of certain glycoforms at each glycosite. Up to June 2020, 14,644 unique N-glycosylation sites, 30,872 unique N-linked glycosite-containing peptides and 7,204 unique N-linked glycoproteins were identified in human (based on outputs at N-GlycositeAtlas 43: http://glycositeatlas.biomarkercenter.org/#). As for O-linked glycosylation, 4,672 unique O-glycosylation sites were identified across the human brain, kidney, T cells, and serum using EXoO 44. In total, 3,369 glycan structures (based on outputs at GlyCosmos Portal: https://glycosmos.org/glytoucans/list) are identified in human. Glycoproteomic databases are emerging, yet we are only beginning to see the tip of the iceberg.
Apart from developing a suitable MS-based analytical approach, advanced computing power is indispensable for the characterization of glycoproteins. Sophisticated algorithms have been developed into software to assist in the interpretation of mass spectra. SEQUEST 45 and the recently developed pFind 46 are dedicated for the high-throughput peptide and protein identification via tandem mass spectrometry. GlycoPep ID 47, GlycoPep DB 48, and GlycoMod 49 are some of the freely accessible web-based programs for glycopeptide analysis. Skyline 50 and MaxQuant 51 are frequently adopted for large-scale quantitative proteomic studies. GlycoWorkBench 52, SimGlycan 53, Cartoonist 54, and MultiGlycan 55 can be used for the interpretation of glycan spectra, UnicarbDB 56 57 holds one of the largest experimental MS/MS databases on released glycans, while Byonic 58, GPQuest 59, and pGlyco 60 61 are developed to analyze intact glycopeptide spectra.
The recent technology advancement has brought numerous innovative approaches in various aspects of analytical glycoproteomics, including sample preparation, enrichment, mass spectrometric analyses, data analysis tools, and databases. As a result, the complexities of glycosylation characterization are reduced to a large extend. Along with the growing attention placed upon the alterations of glycosylation in every biological perturbation, especially in pathological states, the glycosylation “enigma” has been unraveling at a faster pace. Being the center of glycomics, glycoproteomics finally comes to the spotlight of human proteome characterization.
Sri H. Ramarathinam and Anthony W. Purcell, Department of Biochemistry and Molecular Biology and Infection and Immunity Program, Biomedicine Discovery Institute, Monash University, Clayton 3800, Victoria, Australia
Our immune system sources actionable intelligence in the fight against pathogens in many forms including peptides, lipids and other small molecules associated with infection and cancer. The Human Leukocyte Antigen (HLA) proteins, expressed on cell surface, play an important role in conveying the status of cellular health to the immune system by presenting short peptides to T-cells. These short peptides could be from a variety of cellular and extraneous sources forming a snapshot of proteins - synthesized or degraded within the cell. Two major pathways enable antigen presentation: the HLA class I, expressed on all nuclear cells, present endogenous antigen to CD8+ T cells and the HLA class II, found only on professional antigen-presenting cells (such as dendritic cells and macrophages) present antigen from endogenous and exogenous sources to CD4+ T cells (Figure 1).
Specific receptors on T-cells (TCRs) are used to survey the landscape of HLA-peptide ligands on cell surface to find their cognate peptide-HLA complex, much like going through social media feeds to find a specific post of interest. Each TCR can generally recognise a single HLA-peptide complex, due to the remarkable sequence diversity engendered in the TCR through recombination of different genetic elements during T-cell development. T-cells also undergo selection in the thymus such that they are poised to recognise foreign peptides that may arise from viral and bacterial proteins or from inappropriately expressed or somatic mutation-bearing peptides in cancer. Presentation of such foreign peptides in complex with HLA molecules on the surface of infected or malignant cells attracts scrutiny of T-cells bearing the TCR that can recognise this HLA-peptide complex resulting in activation of the immune response and eradication of the cell. The ‘status updates’ in form of immune-related peptides constitutes the ‘immunopeptidome’ of the cells and has been characterised in multiple host species including human, mouse, bat , bovine , swine  and chicken .
The term immunopeptidomics describes the systematic, high-throughput analysis of HLA-bound peptides using mass spectrometry [5-7]. Understanding and deciphering the cellular communication updates (peptide sequences) by the immune system is crucial in the development of new vaccines against viruses as well as immunotherapies against cancer and auto-immune diseases [8-10].
Identifying HLA-peptides involves immunoprecipitation of HLA molecules from cells or tissues followed by separation of peptides from heavy chains, fractionation and subsequent analysis by mass spectrometers . In contrast to global proteomic analysis, the HLA peptides pose unique challenges requiring exacting sample preparation and analysis strategies. There is a need to have dedicated and specialised labs and informatics pipelines to overcome some common challenges. The yield depends on expression of HLA molecules, choice of appropriate methodologies to isolate the peptides, fine tuning of parameters for acquisition of high-quality mass spectrometry data and ultimately appropriate software to interpret data and identify peptide sequences.
One of the biggest hurdles is the amount of material required to do an in-depth immunopeptidomics analysis. To overcome the sample limitation, several algorithms have been developed to predict peptides that bind to specific HLA [12, 13]. While the prediction tools are invaluable, they do not yet consider post-translationally modified (PTM) peptides. Additionally, there is a disparity between peptides identified by mass spectrometry and the top results from prediction algorithms with the majority only explaining at most 10% of peptides as strong and or weak binders. Developments in sample processing and sensitive instrumentation are reducing the need to have large sample sizes and several studies already analysing patient material either individually or in small pools. The HLA-peptides bearing diverse C-termini, for example, may require analysis of singly-charged ions which are traditionally ignored in proteomics workflows .
The software to search the MS data is another area that has contributed significantly to improve the number of peptides identified. There is scope for improvement, especially development of appropriate decoy databases for HLA peptides that tend to have a variety of N- and C-termini and in developing peptide-centric algorithms without any influence of protein grouping. Endogenous processing in cells and HLA type result in varied peptide, requiring significant computing resources during database search.
A community standard of cell lines that can be used to benchmark the complete process (cell line to data) will also be an invaluable tool to improve upon and push the limits of current techniques. Additionally, there is a need for robust well-defined, widely-available synthetic HLA-peptide standards (>1000-5000 peptides) to benchmark various peptide identification and informatics pipelines.
Formation of HUPO-Human Immunopeptidome Project (HUPO-HIPP) in 2015, brought the leaders in the field together to advance research, support collaborative efforts including development of standards for publication [15, 16]. HUPO-HIPP organised two successful events so far, including a summer school and a precision oncology meeting that introduced the techniques and highlighted some key challenges in the path forward. New members are welcome to join us at HUPO-HIPP for latest updates.
In recent times, there is a growing appreciation for presence of PTM peptides  and peptides that are non-genomically templated in addition to the linear peptide sequences. While they challenge known dogmas, peptides from Defective Ribosomal Products (DRIPs) , post-translationally spliced peptides [19, 20] and peptides from UTRs and non-coding regions are worthy of consideration to explore their potential role in health and disease. As a field, tremendous achievements have led to a deeper understanding of the antigen presentation and processing machinery, yet we continue to be surprised by the intricate network of cells and proteins that keep us safe
Figure 1: A) HLA-class I and II molecules play a crucial role in key immunological pathways. Understanding the peptide repertoire offers insight into immunosurveillance machinery and its modulation. B) HLA class I and II pathways present antigen to CD8+ and CD4+ T-cells respectively.
1. Wynne, J.W., et al., Characterization of the Antigen Processing Machinery and Endogenous Peptide Presentation of a Bat MHC Class I Molecule. J Immunol, 2016. 196(11): p. 4468-76.
2. Nielsen, M., T. Connelley, and N. Ternette, Improved Prediction of Bovine Leucocyte Antigens (BoLA) Presented Ligands by Use of Mass-Spectrometry-Determined Ligand and in Vitro Binding Data. Journal of Proteome Research, 2018. 17(1): p. 559-567.
3. Pedersen, L.E., et al., Porcine major histocompatibility complex (MHC) class I molecules and analysis of their peptide-binding specificities. Immunogenetics, 2011. 63(12): p. 821-834.
4. Cumberbatch, J.A., et al., Chicken major histocompatibility complex class II molecules of the B19 haplotype present self and foreign peptides. Animal Genetics, 2006. 37(4): p. 393-396.
5. Caron, E., et al., The structure and location of SIMP/STT3B account for its prominent imprint on the MHC I immunopeptidome. Int Immunol, 2005. 17(12): p. 1583-96.
6. Hunt, D.F., et al., Characterization of peptides bound to the class I MHC molecule HLA-A2.1 by mass spectrometry. Science, 1992. 255(5049): p. 1261.
7. Falk, K., et al., Allele-specific motifs revealed by sequencing of self-peptides eluted from MHC molecules. Nature, 1991. 351(6324): p. 290-296.
8. Engelhard, V.H., et al., MHC-restricted phosphopeptide antigens: preclinical validation and first-in-humans clinical trial in participants with high-risk melanoma. J Immunother Cancer, 2020. 8(1).
9. He, Q., et al., Targeting cancers through TCR-peptide/MHC interactions. Journal of Hematology & Oncology, 2019. 12(1): p. 139.
10. Serra, P. and P. Santamaria, Antigen-specific therapeutic approaches for autoimmunity. Nature Biotechnology, 2019. 37(3): p. 238-251.
11. Purcell, A.W., S.H. Ramarathinam, and N. Ternette, Mass spectrometry-based identification of MHC-bound peptides for immunopeptidomics. Nat Protoc, 2019. 14(6): p. 1687-1707.
12. Jurtz, V., et al., NetMHCpan-4.0: Improved Peptide-MHC Class I Interaction Predictions Integrating Eluted Ligand and Peptide Binding Affinity Data. J Immunol, 2017. 199(9): p. 3360-3368.
13. Peters, B., M. Nielsen, and A. Sette, T Cell Epitope Predictions. Annual Review of Immunology, 2020. 38(1): p. 123-145.
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Ed Nice and Stephen Pennington, co-Chairs, HPP Pathology Resource Pillar
Some of you may have heard already that, due to increased pressures of work due to the COVID-19 pandemic, Prof Dan Chan will stand down as the inaugural Chair of the HPP Pathology Resource Pillar. Dan has been outstanding in the drive and passion he has brought to this role and to getting the Pathology Pillar operational. I am sure you would like to join us in thanking Dan.
We now, of course, need to find a suitable replacement – a new Chair of the HPP Pathology Resource Pillar. The Chair is responsible for developing pillar strategic plans and projects, expanding membership of Pillar and reporting to HPP EC.
Dan has kindly offered to ‘guide’ the incoming Chair, and of course, receive active support from the co-Chairs. If you think you have the necessary drive and enthusiasm for this important HUPO role, please send the following information to HUPO office (office@HUPO.org) by Friday 31st July. This will be a 2 year appointment in the first instance.
i) Proteomics track record
ii) HUPO/HPP track record
iii) Evidence of national/international visibility
iv) Your vision for future development of the HPP Pathology Resource Pillar
v) A one-page CV/bio
vi) Names and contact details of 2 scientific/clinical referees
Thank you for your consideration.
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